PREDIKSI HARGA RUMAH DI JABODETABEK MENGGUNAKAN METODE ARTIFICIAL NEURAL NETWORK

A house is a fundamental need for humans. Determining house prices is a crucial aspect of property transactions, especially in major areas like Jabodetabek, where property prices are consistently rising. Prediction is a suitable tool to assist in decision-making for determining house prices. There are numerous methods that can be applied for prediction; the author employs the Artificial Neural Network (ANN) method. ANN is known as a highly flexible predictive algorithm capable of accommodating various input features. The results of using the ANN method for predicting house prices in the Jabodetabek area show a Mean Absolute Error (MAE) of 0.209, Mean Squared Error (MSE) of 0.159, and Mean Absolute Percentage Error (MAPE) of 4.951.

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Publication Details

Journal
KERNEL Jurnal Riset Inovasi Bidang Informatika dan Pendidikan Informatika
Published
2025-04-26
DOI
https://doi.org/10.31284/j.kernel.2024.v5i2.6806
Primary Topic
Data Mining and Machine Learning Applications
Type
article
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article

PREDIKSI HARGA RUMAH DI JABODETABEK MENGGUNAKAN METODE ARTIFICIAL NEURAL NETWORK

Muhammad Hafizh, Agung Mustika Rizki, Subairi Subairi, Raditya Dimas Libriawan et al.
KERNEL Jurnal Riset Inovasi Bidang Informatika dan Pendidikan Informatika
Data Mining and Machine Learning Applications
article

PREDIKSI HARGA RUMAH DI JABODETABEK MENGGUNAKAN METODE ARTIFICIAL NEURAL NETWORK

Muhammad Hafizh, Agung Mustika Rizki, Subairi Subairi, Raditya Dimas Libriawan, Naufal Duta Maulana
article en

Abstract

A house is a fundamental need for humans. Determining house prices is a crucial aspect of property transactions, especially in major areas like Jabodetabek, where property prices are consistently rising. Prediction is a suitable tool to assist in decision-making for determining house prices. There are numerous methods that can be applied for prediction; the author employs the Artificial Neural Network (ANN) method. ANN is known as a highly flexible predictive algorithm capable of accommodating various input features. The results of using the ANN method for predicting house prices in the Jabodetabek area show a Mean Absolute Error (MAE) of 0.209, Mean Squared Error (MSE) of 0.159, and Mean Absolute Percentage Error (MAPE) of 4.951.

KERNEL Jurnal Riset Inovasi Bidang Informatika dan Pendidikan InformatikaVol. 5(2)
Openalex Percentile: Top 88%
Data Mining and Machine Learning Applications
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PREDIKSI HARGA RUMAH DI JABODETABEK MENGGUNAKAN METODE ARTIFICIAL NEURAL NETWORK — Muhammad Hafizh, Agung Mustika Rizki, et al. · KERNEL Jurnal Riset Inovasi Bidang Informatika dan Pendidikan Informatika (2025) | TGRS Research Map | TGRS